ABSTRACT: Cardiovascular disease (CVD) reportedly causes 31% of global deaths with overwhelming personal and economic costs, the latter estimated as $400 billion annually in the US. Lack of regular screening contributes to severe undertreatment for CVD, with some estimates finding only 1/3 of eligible patients taking preventative medications. One of the most important biomarkers for CVD, elevated blood lipids, requires invasive blood draws followed by lab-based testing. These requirements limit access to screening for many at-risk patients in low resource settings, and make frequent longitudinal monitoring impractical for everyone. Worse still, recent data shows that the temporal dynamics of blood lipids, including postprandial increases, circadian, ultradian (<24 hr cycles), and fluctuations during menstrual cycle, all negatively affect the accuracy of blood lipid test results. Non- invasive methods that more immediately and continuously track blood-lipids would transform CVD monitoring for those at risk. The goal of this project is to develop the first non-invasive optical technology for measuring blood lipids. To accomplish this goal, we will develop a new imaging technique called Short-Wave Infrared Spatial Frequency Domain Imaging (SWIR-SFDI). SWIR-SFDI leverages spectroscopic SWIR patterned illumination combined with model-based analysis to extract tissue optical properties as well as lipid and water concentrations. Compared to both visible (VIS) and near infrared (NIR) imaging, the SWIR wavelength band potentially provides better quantification of lipids and deeper imaging. In this project, we propose to develop SWIR-SFDI instrumentation and processing methodology to demonstrate that triglycerides (TG), cholesterol, LDL-C, and HDL-C, all of which are strong predictors of CVD risk, can be tracked longitudinally with high accuracy. We will fabricate a mobile hyperspectral SWIR-SFDI system with an innovative dual digital micromirror device (DMD) configuration for rapid wavelength tuning and spatial light patterning between 700 ? 1600 nm at high speed. Performance benchmarks include: spectral resolution <6 nm FWHM, 10-? acquisition < 5 sec, ?a and ?s errors <3%, drift (7 hr) <2%. We will also develop a 2-layer skin-model to improve in vivo blood lipid quantification and develop methodology for spectral classification and quantification of TG, cholesterol, LDL-C, and HDL-C and test the accuracy of these algorithms in simulation and by fabricating 3-D printed vascularized phantoms with a range of skin types. Finally, we will conduct a normal volunteer feasibility study to assess the ability of SWIR- SFDI to accurately track postprandial lipids in comparison to traditional laboratory measurement from invasive blood draws. Completion of these aims will enable our team to progress to a larger R01-funded, hypothesis- driven clinical study following the period of this project. Over the longer term, SWIR-SFDI has the potential to transform CVD lipid testing and improve outcomes for patients through: 1.) Better risk-stratification for patients based on frequent measurements, 2.) Unprecedented characterization of circadian and ultradian lipid cycles, 3). More accessible monitoring during therapy, and 4) Development of at-home or wearable blood lipid monitors.